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Senior Data Scientist

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Onsite

Senior Data Scientist

Expert Executive Recruiters (EER Global)

Senior Data Scientist

Skills

SQL QueriesMongoDBData MiningPythonData ScienceRGrafanaData AnalysisMachine Learning

14 days ago

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Important information


Contract type:

Permanent

Location:

Armenia

Work mode:

Onsite

Published on:

11 October 2026

What they need


Senior Data Scientist – Real-Time Programmatic Advertising

We are seeking a Senior Data Scientist for a leading AdTech company whose sell-side omnichannel platform uses AI and 100+ billion daily first-party data signals to deliver hundreds of millions of ads every day.

In this senior, hands-on role, you will work at the core of a high-volume, real-time programmatic system processing over 2 billion requests per day. Your work will directly drive campaign optimization at scale through production ML systems, not offline research.

Responsibilities

  • Analyze large, complex datasets to uncover hidden patterns and opportunities
  • Build and own end-to-end, highly scalable data pipelines
  • Develop state-of-the-art ML models and algorithms for monetization
  • Provision data models for real-time (online) processing
  • Shape new data products and continuously improve existing ones
  • Partner with Product, BI, Analytics, DevOps, R&D and Marketing to deliver end-to-end solutions
  • Own full releases to production, from requirements analysis and testing through monitoring, measuring results, and responding quickly to critical issues

Requirements – Must

  • B.Sc. or M.Sc. in Computer Science, Engineering, Mathematics, Statistics or a related field
  • 6+ years as a Data Scientist with a strong grounding in ML concepts and models
  • Hands-on Python experience with data science and ML libraries (e.g., XGBoost, LightGBM, regression and classification, recommendation systems)
  • Solid SQL and database knowledge for data retrieval
  • Experience with monitoring and alerting tools (e.g., Grafana, Kibana)

Advantage

  • Knowledge of the programmatic advertising landscape (DSPs, SSPs, exchanges), which is a significant advantage
  • Experience with relational (e.g., Vertica, VoltDB) and non-relational (e.g., MongoDB) databases
  • Experience with PMML

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